Characteristics of salivary telomere length shortening in preterm infants

Objective To examine the association between gestational age, telomere length (TL) and rate of shortening in newborns. Study design Genomic DNA was isolated from buccal samples of 39 term infants at birth and one year and 32 preterm infants at birth, term-adjusted age (40 weeks post-conception) and age one-year corrected for gestational duration. Telomere length was measured by quantitative real-time PCR. Demographic and clinical data were collected during clinic or research visits and from hospital records. Socioeconomic status was estimated using the deprivation category (DEPCAT) scores derived from the Carstairs score of the subject’s postal code. Results At birth, preterm infants had longer telomeres than infants born at term. However, there was no difference in telomere length between preterm infants and term infants at one year of age, implying that the rate of telomere shortening was greater in pre-term than term infants. Interestingly, TL at age 40 weeks post-conception in preterm infants was significantly longer than term infant TL at birth, suggesting that time since conception is not the only factor that affects rate of shortening. Several factors, including sex, fetal growth restriction, maternal age, maternal booking body mass index (BMI), mother education level and DEPCAT score, also differed between the preterm and term groups. Conclusions Preterm infants have longer telomeres than term infants at birth. In the studied cohort, the rate of telomere shortening was greater in the premature group compared with the term infants. This finding agrees with previous studies using cord blood, suggesting that the longer TL in premature infants detected at birth do not persist and demonstrating that use of saliva DNA is acceptable for studies of telomere dynamics in infants. However, that the TL at age 40 weeks post-conception in preterm is longer than term infants at birth suggests that biological factors other than time since conception also affect rate of shortening.

Introduction Preterm birth is defined by the World Health Organization as birth before 37 completed weeks of gestation [1]. Between March 2017 and March 2018 in Scotland, 8.3% of all births (6.6% live singleton births and 68% of live multiple pregnancy births) were premature in contrast to the 1970's when approximately 5.5% (5.0% of singleton live and 32.9% of multiple live births) were premature [2]. This increase in preterm births has been attributed in part to increases in the occurrence of multiple births due to assisted reproductive techniques, non-spontaneous preterm deliveries due to improvements in maternity and neonatal care, maternal age, and underlying maternal health issues such as diabetes and high blood pressure [2][3][4][5].
Studies of TL in preterm infants suggest that preterm infants have longer telomeres than term infants and that telomere shortening is more rapid in preterm infants than term. Friedrich et al. [46] observed that umbilical cord blood DNA telomere length at 32 weeks gestation was significantly shorter than that at 27 weeks. Vasu et al. [47] found that preterm infants (defined as < 32 weeks gestation) had significantly longer telomeres at birth and at term equivalent age than term infants in leucocytes. TL was also negatively correlated with birth weight and positively correlated with maternal age.
The current study extends these findings by measuring telomere length of buccal DNA from a cohort of preterm infants (n = 32) collected at birth, term age, and one year and term infants (n = 39) at birth and one year. We compared maternal and birth characteristics, socioeconomic and health factors, telomere length and telomere length shortening between the two groups and within groups. To our knowledge, this is the first study to compare telomere length from buccal samples in preterm and full-term infants at these time points and longitudinally.

Characteristics of the preterm and term groups
Saliva samples were obtained for telomere length analysis from 35 preterm infants and 39 term infants. The maternal and infant characteristics differed between the two groups (Table 1). There were more males in the preterm group (p < 0.05) and the preterm infants had lower birth weight Z-scores indicating fetal growth restriction (p < 0.05). Neither paternal age nor incidence of identified maternal chronic illness differed between the term and preterm groups. The average age of the mothers of preterm infants was 31.6 years and of term infants was 35.3 years (95% confidence interval (CI) -6.3 to -1.3, p = 0.004). The mothers of preterm infants had a higher body mass index (BMI) > 30; p = 0.009). Of mothers of preterm infants, 31.4% smoked cigarettes during pregnancy compared with 5.1% of mothers of term infants (p = 0.004). Mothers of term infants were more likely to have attended post-secondary school (p < 0.001), and to live in a postal code sector ascribed a deprivation category score (DEPCAT) greater than or equal to 3 (affluent; p = 0.005).

Telomere length comparisons: Preterm and term groups
Preterm infants had significantly longer telomeres than term infants at birth (mean difference of 2.9 kb/telomere, p < 0.005, n = 36 and 23, respectively for term and preterm infants; Fig 1; Table 2). Moreover, the mean telomere length of preterm infants remained longer at termadjusted age than the term infant telomere lengths at birth (mean difference of 1.9 kb/telomere, t = 2.347, CI: 0.021 to 0.264, df = 64.97, p = 0.022, n = 36 and 31, respectively for term and preterm infants). The difference between telomere length at birth and term-adjusted age for the preterm infants was not significant (paired t-test: t = 1.240, df = 19, p = 0.230, n = 20; power analysis: power = 0.8, effect size = 0.58, alpha = 0.05). By one year corrected full term age, however, telomere lengths between the term and preterm groups were no longer significantly different (t = 0.9657, df = 53.08, p = 0.339, n = 32 and 28, respectively for term and preterm infants; Table 2). Telomeres were significantly shorter in both the term and the preterm groups at one year of age compared with birth ( Table 2, average difference of 4.3 kb/diploid genome, t = 6.223, df = 17, p < .001 and 2.0 kb/telomere, t = 5.642, df = 29, p < 0.001, respectively for the preterm Telomere length is negatively associated with gestational age at birth, but not by one year of age. Absolute telomere length vs gestational age at birth (left panel), term-adjusted age (middle panel) and one year of age (right panel). Black circles and gray triangles represent samples from preterm and term individuals, respectively. Horizontal black lines represent the median TL for each group and boxes represent the interquartile range. Significant differences in TL as determined by t test are indicated.  Tables 2 and  3) during the first year of life. While TL at birth was also inversely correlated with birth weight (r = 0.306, df = 57, p = 0.018), this is not the case when using the birthweight z-score (r = -0.006, df = 57, p = 0.962), suggesting that the correlation between birth weight and TL is due to the very high correlation between GA and birthweight. The correlation between the telomere length at birth and one year for all infants was 0.55 (p < 0.001, df = 46). This was likely driven by the term infants because the correlation between telomere length at birth and one year of age for term infants was 0.634 (p < .001, df = 28) but was lower (0.374, df = 16) and not statistically significant (p = 0.126) in preterm infants.

PLOS ONE
and S2 Tables, respectively. There was no significant association between any of the variables listed in Table 1 and TL at birth when analysis was limited to the term infants. There was no significant association with socioeconomic status. Similar results were observed if z-scored Telomere shortening is greater in preterm infants than term infants. The difference in telomere length between age one and birth vs gestational age at birth in preterm (triangles) and term (circles) infants. Horizontal black lines represent the median TL difference and boxes represent the interquartile range for each group. Significant difference in TL shortening as determined by t test is indicated.

Discussion
Telomere length was measured in genomic DNA from buccal swabs collected from very preterm infants during the first week after birth, at term-adjusted age and at year one. These values were compared with telomere lengths of genomic DNA isolated from buccal swabs collected from apparently healthy term infants during the first week after birth and at one year. As described previously [48], risk factors for premature birth, high booking BMI, male fetal sex, fetal growth restriction [49], and exposure to cigarette smoke [50,51], were enriched in the preterm group of infants compared with the term group (Table 1). These risk factors are also associated with shorter telomere lengths [52][53][54][55]. Compared with mothers of term infants, mothers of preterm infants were less likely to have post-secondary education or live in an affluent neighborhood. The mothers of term children were older than those of preterm children in contrast to what has been previously described [48], however this was attributed to recruitment. Consistent with previous cross-sectional studies in leukocytes from venous [47,56] or cord blood [57,58], we found that saliva-derived telomere lengths were longer in preterm infants (both at birth and at term-adjusted age) compared with term infants at birth. Telomere shortening was more rapid in the preterm cohort than in term infants. In contrast with a previous study [47], the shortening rate in the preterm group was not significantly associated with gestational age or birthweight. This may be due to the larger sample size of the current study (n = 16 compared with n = 5), technical differences [59], or that this study utilized DNA from buccal cells whereas the previous study used blood. While data from a cross-sectional study suggests that the rate of telomere shortening is similar in neutrophils and T cells [60], it is possible that telomere shortening rates differ in the various cell populations (depending on cell replication rates and telomerase activity) comprising buccal samples and this may affect the ability to detect such a difference.
A few studies have compared differences in telomere length in groups of children or adolescents born prematurely or at term [61,62]. Neither Hadchouel et al. (2015) nor Henckel et al. (2018) found statistically significant differences in telomere length measured from samples taken approximately at age 10 or 14.9 years, respectively. Indeed, in our study, the difference in telomere length between the samples collected at one year of age did not differ between the term or preterm groups in this study. The sample size was sufficient to detect longer telomeres in the preterm group at birth (term), term-adjusted (preterm) or one year at a medium effect size d (0.65) with a 5% Type I error and power of 0.80. While this is not the first study to examine telomere length in buccal samples from preterm infants [63], this is the first to demonstrate that telomere lengths in buccal samples collected from term infants at birth were shorter than telomere lengths from preterm infants collected at birth and term-adjusted age.
Evidence suggests that the intrauterine environment influences newborn TL and our study confirms that maternal health is associated with TL among preterm but not (in our study) in term births. TL in cord blood from infants born to mothers experiencing high psychosocial stress during pregnancy were shorter than infants born to low-stress mothers [64][65][66]. Another study, consisting of 1026 mother-infant pairs, demonstrated a negative association between socioeconomic status (SES) and cord blood TL [67]. Maternal folate level is positively associated [68], and maternal smoking has been negatively associated [69] with umbilical cord blood TL. In the current study, maternal smoking was not associated with shorter telomeres at birth, nor was it associated with more rapid TL shortening. There was also no difference between male and female newborns or DEPCAT status. Post-hoc power analysis indicated that this was likely due to sample size (S5 Table). All mothers in the study, except for three of the mothers of preterm infants, took folic acid during pregnancy and so it is difficult to assess a relationship between folic acid and TL. In contrast, preterm infants born to mothers experiencing chronic illness had shorter telomeres. This is difficult to interpret, given that several conditions were defined as chronic illness in the study, including mental illness, type 2 diabetes, epilepsy, hypothyroidism, among others. Maternal age was positively associated with TL in preterm infants (Table 4). This is consistent with the findings of Vasu et al. [47] and Okuda et al. [70]. This finding was robust to the inclusion of maternal education and maternal chronic illness in the model, indicating that the relationship between TL at birth and maternal age cannot be explained by socioeconomic factors.
Additional research examining the relationship between environment and TL in neonates, especially those born prematurely, is needed. Although still relatively small, our study consists of one of the largest cohorts with TL measured longitudinally at birth and one year for term and preterm infants and term-adjusted age for preterm infants. Our findings indicate more rapid TL shortening in preterm infants, perhaps reflecting that birth occurred prior to a late term burst of growth and cellular replication. Future research should aim to identify the biological processes behind these findings.

Study participants
A cohort of 50 preterm infants (< 32 weeks gestation) and 40 term control infants (37-42 weeks gestation) were recruited during the first week of age from the Simpson Centre for Reproductive Health, Edinburgh, UK Royal Infirmary of Edinburgh as previously described [48]. Most of the parents of the term babies were approached prior to delivery. None of the term babies had suspected or proven fetal anomaly or proven infection. The term infants were apparently healthy with the exception of one who had jaundice. The term babies stayed in the hospital for an average of 4.5 days (range 2-9) with their mothers. Ethical approval was obtained from the South East Scotland Research Ethics Committee (Reference 11/AL/0329). NHS management approval was obtained (Lothian R&D Project number 2011/R/ NE/03). Infant samples were collected under the framework of the Edinburgh Reproductive Tissue Bio-Bank (West of Scotland Research Ethics Service Reference 09/S0704/3) following an amendment to ethical approval (Reference AM07/1). All parents gave written informed consent, and all studies were performed in accordance with the Declaration of Helsinki. Term controls were born at least 37 completed weeks post last menstrual period (LMP) with no identified maternal or fetal complications. In the control group, only women with singleton pregnancies, without pre-existing hypertension or diabetes and who were non-smokers in the current pregnancy were included. Demographic and clinical data were collected from hospital and research visits and hospital records. From the main cohort, there were 32 preterm and 39 term infants with available DNA for the TL assay. The characteristics of this smaller group are described in Table 1. Socioeconomic status is approximated using deprivation category (DEPCAT) scores derived from the Carstairs score of the subject's postal code [71]. The DEPCAT scores are categorical variables ranging from 1-7 with 1 and 2 being the most affluent.

Sample collection
Saliva for DNA was collected from the preterm infants at birth; at term-adjusted age); and at one year corrected; and from term infants at birth and one year of age. Samples were collected from preterm infants within a median of 3 days (interquartile range (IQR) of 1.75-4 days from birth) and term infants within a median of 2 days (IQR of 1-2.3 days) from birth. Saliva was collected using the Oragene DNA (OG-250) kits and saliva sponges CS-1 and extracted using prepIT-2LP (DNA Genotek, Ottawa, ON, Canada). DNA was quantified using the Qubit 2.0 Fluorometer (Life Technologies, Paisley, UK) and stored at -20˚C until received by the Notterman laboratory, where it was stored at -80˚C.

Telomere length
TL was measured by absolute quantitative real-time PCR (qPCR) [72][73][74][75]. Two double stranded oligonucleotides (Integrated DNA Technologies), an 84-mer consisting of (TTAGG) 16 and a 79-mer containing sequence from the 36B4 gene were used to construct standard curves to determine absolute telomere length and number of diploid genomes copies, respectively. TL and single copy gene qPCR assays were performed on separate plates. Each sample was assayed in triplicate and the results averaged. Individual TL was determined by dividing the telomere length per genome by 92, the number of telomeres per diploid genome. Each plate contained DNA from a cell line with a relatively short telomere length (3C167b) [76] and a fibroblast cell line containing a stable integration of TERT, which encodes the protein component of telomerase (NHFpreT) [77]. These were used to control for inter-plate variation as described [73,74]. Human genomic DNA was also included to determine the coefficient of variation (0.09) [73,74]. The intraclass correlation coefficients (calculated using the Ct values) were 0.975 (CI 0.968-0.981) and 0.949 (CI 0.934-0.961), respectively for the telomere and 36B4 technical replicates.

Statistical analysis
Power analysis was performed with G � Power version 3.1.9.6 [78,79] and the R pwr package [80]. All other statistical analysis was performed using R version 4.0.5 [81]. Body mass index was analyzed as either a continuous variable or converted to a categorical variable. Data were tested for normality using the Shapiro-Wilk test. The primary outcome, telomere length, was not normally distributed and was natural log transformed for analysis. One percent was trimmed off both tails of the sample to remove outliers. After transformation, data was normally distributed. Telomere shortening was calculated by subtracting telomere length at term age (or age one from telomere length at birth or term age as indicated. Differences were calculated using untransformed telomere length value. Telomere shortening values were normally distributed.
Supporting information S1 project and mentored CP. We also would like to thank members of the laboratories for comments and discussion.
We acknowledge the support of the British Heart Foundation and the Edinburgh Reproductive Tissue BioBank.